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For Companies At a Glance
- Tasks: Build credit risk models and scorecards using SQL and Python.
- Company: Join a dynamic lending fintech in London, shaping the future of finance.
- Benefits: Enjoy a hybrid work environment with a competitive salary up to £80,000.
- Why this job: Make an impact in a fast-paced industry while developing your data science skills.
- Qualifications: Strong background in credit risk models and proficiency in SQL and Python required.
- Other info: Ideal for those with a numeric degree from a top university.
The predicted salary is between 48000 - 64000 £ per year.
Job Description
Credit Risk Data Scientist
London
Hybrid
Up to £80,000
The Company
I am hiring for a lending fintech based in London who are looking to bring in a Credit Risk Data Scientist to build decision scorecards across the credit risk customer lifecycle.
The Role
What you will do as a Credit Risk Data Scientist:
- Developing scorecards across the credit risk customer lifecycle
- Analyse large datasets to extract meaningful insights to drive model development.
- Developing models working with other functions for collections and acquisitions scorecards
- Communicating and presenting analysis and insights to senior stakeholders across the company
- Using Python daily to develop credit risk models and improve the credit risk scorecard models across the customer lifecycle.
Requirements:
What you need to be successful as a Credit Risk Data Scientist:
- Strong experience working within credit risk models.
- Experience at a fintech/fast-paced company
- Experience developing credit risk scorecards end-to-end.
- Strong experience developing credit models end-to-end.
- Strong experience using Python to develop models.
- Numeric degree from a top university.
Benefits
Up to £80,000 + competitive bonus and benefits
HOW TO APPLY
Please register your interest by sending your CV to Sean Tunley via
#J-18808-Ljbffr
Credit Risk Data Scientist employer: ZipRecruiter
Contact Detail:
ZipRecruiter Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Data Scientist
✨Tip Number 1
Make sure to showcase your experience with credit risk models in your conversations. Be ready to discuss specific projects where you've developed scorecards or pricing models, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Familiarize yourself with the latest trends in fintech and credit risk analytics. Being able to discuss current industry challenges and innovations can set you apart during interviews.
✨Tip Number 3
Practice your SQL and Python skills before the interview. You might be asked to solve a problem or analyze a dataset on the spot, so being sharp in these areas is crucial.
✨Tip Number 4
Network with professionals in the fintech space. Attend relevant meetups or webinars to connect with others in the industry, which could lead to valuable insights or referrals for the position.
We think you need these skills to ace Credit Risk Data Scientist
Some tips for your application 🫡
Understand the Role: Make sure you fully understand the responsibilities of a Credit Risk Data Scientist. Familiarize yourself with scorecard development, model analysis, and the use of SQL and Python in credit risk.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience with credit risk models, particularly in fintech environments. Mention specific projects where you've developed scorecards or pricing models.
Showcase Technical Skills: Clearly outline your proficiency in SQL and Python. Provide examples of how you've used these tools to develop credit risk models or analyze large datasets in your previous roles.
Tailor Your Application: Customize your application materials to reflect the job description. Use keywords from the listing, such as 'credit risk customer lifecycle' and 'end-to-end model development', to demonstrate your fit for the role.
How to prepare for a job interview at ZipRecruiter
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL and Python in detail. Bring examples of projects where you've developed credit risk models or scorecards, and be ready to explain your thought process and the impact of your work.
✨Understand the Credit Risk Landscape
Familiarize yourself with the current trends and challenges in credit risk management, especially within fintech. This will help you demonstrate your knowledge and passion for the field during the interview.
✨Prepare for Case Studies
You may be asked to solve a case study or a technical problem during the interview. Practice analyzing datasets and developing models on the spot, as this will showcase your analytical skills and ability to think critically under pressure.
✨Highlight Collaboration Experience
Since the role involves working with other functions, be ready to discuss your experience collaborating with cross-functional teams. Share specific examples of how you've worked with others to develop models or improve processes.
